Parameter identifiability analysis: Mitigating the non-uniqueness issue in the inverse identification of an anisotropic yield function
Tài liệu tham khảo
Aquino, 2019, Design of heterogeneous mechanical tests: Numerical methodology and experimental validation, Strain, 55, 10.1111/str.12313
Bambach, 2015, Assessing and ensuring parameter identifiability for a physically-based strain hardening model for twinning-induced plasticity, Mech. Mater., 84, 127, 10.1016/j.mechmat.2015.01.019
Banabic, 2010
Barick, 2020, On the uniqueness of intrinsic viscoelastic properties of materials extracted from nanoindentation using FEMU, Int. J. Solids Struct., 202, 929, 10.1016/j.ijsolstr.2020.03.015
Barlat, 2003, Plane stress yield function for aluminum alloy sheets—part 1: theory, Int. J. Plast., 19, 1297, 10.1016/S0749-6419(02)00019-0
Beck, 1977
Beck, 1987, Water quality modeling: A review of the analysis of uncertainty, Water Resour. Res., 23, 1393, 10.1029/WR023i008p01393
Bertin, 2016, Integrated digital image correlation applied to elastoplastic identification in a biaxial experiment, The Journal of Strain Analysis for Engineering Design., 51, 118, 10.1177/0309324715614759
Belhabib, 2008, Heterogeneous tensile test on elastoplastic metallic sheets: Comparison between FEM simulations and full-field strain measurements, Int. J. Mech. Sci., 50, 14, 10.1016/j.ijmecsci.2007.05.009
Beveridge, 1970
Brun, 2001, Practical identifiability analysis of large environmental simulation models, Water Resour. Res., 37, 1015, 10.1029/2000WR900350
Cooreman, 2008
Coppieters, 2018, Inverse Yield Locus Identification using a biaxial tension apparatus with link mechanism and displacement fields, InJournal of Physics: Conference Series., 1063
Coppieters, 2018, On the synergy between physical and virtual sheet metal testing: calibration of anisotropic yield functions using a microstructure-based plasticity model, Int. J. Mater. Form., 12, 741, 10.1007/s12289-018-1444-1
Denys, 2016, Multi-DIC setup for the identification of a 3D anisotropic yield surface of thick high strength steel using a double perforated specimen, Mech. Mater., 100, 96, 10.1016/j.mechmat.2016.06.011
Fossum, 1997, Parameter estimation for an internal variable model using nonlinear optimization and analytical/numerical response sensitivities, J. Eng. Mater. Technol., 119, 337, 10.1115/1.2812267
Gábor, 2017, Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems, BMC Syst. Biol., 11, 1, 10.1186/s12918-017-0428-y
Gothivarekar, 2020, Advanced FE model validation of cold-forming process using DIC: Air bending of high strength steel, Int. J. Mater. Form., 13, 409, 10.1007/s12289-020-01536-1
Grama, 2015, On the identifiability of Anand visco-plastic model parameters using the Virtual Fields Method, Acta Mater., 86, 118, 10.1016/j.actamat.2014.11.052
Güner, 2012, Characterization of anisotropy of sheet metals employing inhomogeneous strain fields for Yld 2000–2D yield function, Int. J. Solids Struct., 49, 3517, 10.1016/j.ijsolstr.2012.05.001
Hapsari, 2018, Instrumented Incremental Sheet Testing for material behavior extraction under very large strain: Information richness of continuous force measurement, Mater. Des., 140, 317, 10.1016/j.matdes.2017.12.002
Hartmann, 2018, Identifiability of material parameters in solid mechanics, Arch. Appl. Mech., 88, 3, 10.1007/s00419-017-1259-4
Hartmann, 2021, Material parameter identification using finite elements with time-adaptive higher-order time integration and experimental full-field strain information, Comput. Mech., 1–18
Hippke, 2020, Optimized and validated prediction of plastic yielding supported by cruciform experiments and crystal plasticity, Int. J. Mater. Form., 13, 841, 10.1007/s12289-020-01569-6
ISO 16842:2021 Metallic materials- sheet and strip –Biaxial tensile testing using a cruciform test piece.
Jones, 2018, Parameter covariance and non-uniqueness in material model calibration using the Virtual Fields Method, Comput. Mater. Sci., 152, 268, 10.1016/j.commatsci.2018.05.037
Kleissen, 1990, The identifiability of conceptual hydrochemical models, Water Resour. Res., 26, 2979, 10.1029/WR026i012p02979
Kuwabara, 2011, Effect of anisotropic yield functions on the accuracy of hole expansion simulations, J. Mater. Process. Technol., 211, 475, 10.1016/j.jmatprotec.2010.10.025
Kuwabara, 2017, Material modeling of 6016-O and 6016–T4 aluminum alloy sheets and application to hole expansion forming simulation, Int. J. Plast., 93, 164, 10.1016/j.ijplas.2016.10.002
Kuwabara, 2013, Multiaxial tube expansion test method for measurement of sheet metal deformation behavior under biaxial tension for a large strain range, Int. J. Plast., 45, 103, 10.1016/j.ijplas.2012.12.003
Lattanzi, 2020, Inverse identification strategies for the characterization of transformation-based anisotropic plasticity models with the non-linear VFM, Int. J. Mech. Sci., 173, 10.1016/j.ijmecsci.2020.105422
Lava, 2009, Assessment of measuring errors in DIC using deformation fields generated by plastic FEA, Opt. Lasers Eng., 47, 747, 10.1016/j.optlaseng.2009.03.007
Lecompte, 2009, Parameter identification for anisotropic plasticity model using digital image correlation: Comparison between uni-axial and bi-axial tensile testing, European Journal of Computational Mechanics/Revue Européenne de Mécanique Numérique, 18, 393
Levenberg, 1944, A method for the solution of certain non-linear problems in least squares, Q. Appl. Math., 2, 164, 10.1090/qam/10666
Maček, 2020, Calibration of advanced yield criteria using uniaxial and heterogeneous tensile test data, Metals., 10, 542, 10.3390/met10040542
Magnus, 2001, Thermo-elastic-viscoplastic modeling of IN792, Journal of the mechanical behavior of materials., 12, 359, 10.1515/JMBM.2001.12.6.359
Mahnken, 1996, Parameter identification for viscoplastic models based on analytical derivatives of a least-squares functional and stability investigations, Int. J. Plast., 12, 451, 10.1016/S0749-6419(95)00016-X
Mahnken, 2017, 1
Marek, 2019, Extension of the sensitivity-based virtual fields to large deformation anisotropic plasticity, Int. J. Mater. Form., 12, 457, 10.1007/s12289-018-1428-1
Marquardt, D. W., 1963. An algorithm for least-squares estimation of nonlinear parameters. Journal of the society for Industrial and Applied Mathematics. 11(2), 431-441. .
MatchID., 2021. Available online: https://www.matchid.eu/Software.html (accessed on 4 February 2021).
Notta-Cuvier, 2013, Identification of Johnson-Cook's Viscoplastic Model Parameters Using the Virtual Fields Method: Application to Titanium Alloy Ti6Al4V, Strain, 49, 22, 10.1111/str.12010
Oliveira, M.G., Thuillier, S. and Andrade-Campos, A., 2021. Evaluation of heterogeneous mechanical tests for model calibration of sheet metals. The Journal of Strain Analysis for Engineering Design, p.03093247211027061. https://doi.org/10.1177/03093247211027061.
Phadikar, 2013, On the uniqueness and sensitivity of indentation testing of isotropic materials, Int. J. Solids Struct., 50, 3242, 10.1016/j.ijsolstr.2013.05.028
Pierron, 2021, Towards Material Testing 2.0. A review of test design for identification of constitutive parameters from full-field measurements, Strain, 57, 10.1111/str.12370
Prates, 2015, On the equivalence between sets of parameters of the yield criterion and the isotropic and kinematic hardening laws, Int. J. Mater. Form., 8, 505, 10.1007/s12289-014-1173-z
Renner, 2020, Identifiability of single crystal plasticity parameters from residual topographies in Berkovich nanoindentation on FCC nickel, J. Mech. Phys. Solids, 138, 10.1016/j.jmps.2020.103916
Richard, 2013, Viscoelastic modeling and quantitative experimental characterization of normal and osteoarthritic human articular cartilage using indentation, J. Mech. Behav. Biomed. Mater., 24, 41, 10.1016/j.jmbbm.2013.04.012
Rossi, 2016, Application of the virtual fields method to large strain anisotropy plasticity, Int. J. Solids Struct., 97, 322, 10.1016/j.ijsolstr.2016.07.015
Rossi, 2016, Application of the virtual fields method to large strain anisotropic plasticity, Int. J. Solids Struct., 97, 322, 10.1016/j.ijsolstr.2016.07.015
Safa, 2021, Identifiability of tissue material parameters from uniaxial tests using multi-start optimization, Acta Biomater., 123, 197, 10.1016/j.actbio.2021.01.006
Salehghaffari, 2012, A new approach for determination of material constants of internal state variable based plasticity models and their uncertainty quantification, Comput. Mater. Sci., 55, 237, 10.1016/j.commatsci.2011.11.035
Sewerin, 2020, On the local identifiability of constituent stress–strain laws for hyperelastic composite materials, Comput. Mech., 65, 853, 10.1007/s00466-019-01798-w
Souto, 2017, Mechanical design of a heterogeneous test for material parameters identification, Int. J. Mater. Form., 10, 353, 10.1007/s12289-016-1284-9
Souto, 2015
Takizawa, 2018, Development of the User Subroutine Library “Unified Material Model Driver for Plasticity (UMMDp)” for Various Anisotropic Yield Functions, J. Phys. Conf. Ser., 1063, 10.1088/1742-6596/1063/1/012099
Teaca, 2010, Identification of sheet metal plastic anisotropy using heterogeneous biaxial tensile tests, Int. J. Mech. Sci., 52, 572, 10.1016/j.ijmecsci.2009.12.003
Transtrum, 2010, Why are nonlinear fits to data so challenging?, Phys. Rev. Lett., 104, 10.1103/PhysRevLett.104.060201
Van den B., Ton, J. H., Anthony b., et al., 2016. Parameter reduction for the Yld2004-18p yield criterion.International journal of material forming, no. 2, p: 175-178. .
Wang, Yueqi., 2015. Uncertainty quantification of digital image correlation and the impact on material identification. PhD thesis.
Zhang, 2019, Inverse identification of the post-necking work hardening behaviour of thick HSS through full-field strain measurements during diffuse necking, Mech. Mater., 129, 361, 10.1016/j.mechmat.2018.12.014
Zhang Y., Coppieters S., Gothivarekar, S., et al., 2021. Gothivarekar S, et al. Independent Validation of Generic Specimen Design for Inverse Identification of Plastic Anisotropy. International Conference on Material Forming, Esaform2021.
Zhang, 2022, Enhancing the information-richness of sheet metal specimens for inverse identification of plastic anisotropy through strain fields, Int. J. Mech. Sci., 214, 10.1016/j.ijmecsci.2021.106891
